Back
Strong brand, mid-level generalist title, Bengaluru metro location, and popular GenAI skills drive high competition.
Specialized LLM, graph, and production ML requirements limit cross-industry transferability.
Explicit 5+ years and 3+ relevant years plus mandatory LLM, graph, cloud, and MLOps skills create stringent filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead applied research and product-oriented data science within Agentic AI platform initiative, focusing on domain-specific model evaluation, fine-tuning, and operationalization.
Design and implement evaluation frameworks, knowledge graphs, embeddings, and inference engines to enable semantic search, reasoning, and scalable AI deployment.
Collaborate with engineering and business teams to deploy scalable AI solutions in production environments and communicate findings across teams.
Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
5+ years of overall IT experience with 3+ years in applied machine learning or NLP, including hands-on production experience.
Strong experience with LLMs, Generative AI, fine-tuning, evaluation, and proficiency in Python with ML libraries like PyTorch, TensorFlow, Scikit-learn.
Experience with graph databases (e.g., Neo4j, DGL), knowledge graphs, vector stores, cloud AI/ML services (AWS, Azure, or GCP), and MLOps practices.
Experienced in handling business unit-specific AI/ML problem statements and delivering value through agentic AI workflows and domain-specific LLM solutions.
Technically adept in foundational model evaluation, prompt optimization, data curation, and anomaly detection within generative AI and agentic AI domains.
Capable of independently driving cross-functional collaboration involving engineering, platform, and business stakeholders to operationalize AI/ML models in production.